Design of Traffic Volume Forecasting based on Genetic Algorithm

Abstract

The traffic flow forecasting is very important aspect of traffic predication and congestion. It alleviates the increasing congestion problems that cause drivers to shorten the travelling duration required and prevent financial loss. Increasing congestion is one of the severe problems in big city areas. The aspect of traffic prediction is that it may give drivers to plan their traveling time and traveling path, based on the predictive data information they have. The aim is to design locally weighted regression model by proposing a method, which is a combination of Genetic algorithm and locally weighted regression method. This model helps to achieve optimal prediction performance under various traffic condition parameters. The time series model is used to predict the forecast value for the accurate assumption of the traffic volume generation according to the road capacity. The GA model results show these kind of predictions always be useful for highway road authorities.

The Design of The Alumni and Career Development Center (ACDC) Application at Faculty of Engineering, Universitas Negeri Medan

“…Employer is user who can send job vacancies directly to the system at the same time they can see job seeking candidates who meet the specified requirements. The UML is used in this study to achieve good application design, because it can reduce typical encoding errors and increase the effectiveness and efficiency of software development time [1]. The roles of the 3 types of users can be seen in the following use case image:…”